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A Method to Represent a Well in a Three-Dimensional Discrete Fracture Network Model
Hai Pham, Rishi Parashar1, Nicole Sund1
1Division of Hydrologic Sciences, Desert Research Institute, 2215 Raggio Parkway, Reno, NV, 89512.
Ground Water
|July 7, 2020
Summary
This study introduces a new method for modeling wells in discrete fracture networks (DFNs). The approach ensures connectivity between wells and fracture backbones, improving flow and transport simulations in fractured rock.
Area of Science:
- Geosciences
- Hydrogeology
- Computational modeling
Background:
- Discrete fracture network (DFN) models often simplify or omit wells, leading to disconnects between wells and the hydraulically active fracture network.
- Ignoring smaller fractures and isolated networks in DFNs can result in large impermeable rock matrices and poor well connectivity.
Purpose of the Study:
- To develop and validate a novel method for incorporating wells into 3D DFN models.
- To enhance the accuracy of flow and transport simulations by ensuring well connectivity to fracture backbones.
Main Methods:
- Conceptualized wells in 3D DFNs using two orthogonal rectangular fractures aligned with the well axis.
- Introduced six parameters to define well screen, skin zone, and connectivity to fracture backbones.
- Discretized fractures with a high-resolution mesh for improved simulation quality and implemented within dfnWorks 2.0.
Main Results:
- Successfully incorporated wells into 3D DFNs, enabling particle tracking between injection and pumping wells.
- Verified the method against MODFLOW/MODPATH, achieving perfect agreement in hydraulic head and particle tracking simulations.
- Demonstrated the method's ability to ensure well-fracture connectivity and accurately represent flow and transport processes.
Conclusions:
- The developed method effectively integrates wells into DFN models, enhancing simulation accuracy.
- The approach provides a robust framework for understanding fluid flow and solute transport in fractured porous media.
- Recommendations are provided for parameter estimation in real-world applications.
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